CN102788580A - Flight path synthetic method in unmanned aerial vehicle visual navigation - Google Patents

Abstract

The invention studies a flight path synthetic method in an unmanned aerial vehicle visual navigation system. During navigation information acquisition by image characteristic matching, the rotation problem of the unmanned aerial vehicle can not be ignored. According to the invention, euler angles and angular velocity measured by an inertial navigation system is used for the compensation of rotation effect, and then a complete flight path based on visual information is synthesized according to a movement track of a road sign in the image. The position information of the unmanned aerial vehicle is resolved by the image (pixel displacement) coordinate transformation relation of the natural road sign within a certain time interval. The flight path synthetic method in unmanned aerial vehicle visual navigation studied in the invention is suitable for the characteristics of high positioning precision, micromation and low cost of small and medium-size unmanned aerial vehicles, and has theoretic and practical value.

Description

Flight path synthetic method in the navigation of unmanned plane vision

Technical field

The invention belongs to the vision guided navigation field, relate to the flight path Study of synthesis method in a kind of unmanned plane vision navigation.

Background technology

Unmanned plane (UAV) militarily with civilian on effect increasingly important, advanced navigational system is that the decision unmanned plane is accomplished combat duty, improved the key of viability.Over past ten years; No matter still make substantial progress in the development aspect autonomous information processing and the unmanned plane load in location, tracking; Like modern satellite navigation technology, inertial navigation system, communication and monitoring technique etc.; In addition, new visually-perceptible and treatment facility also are provided on the unmanned plane.Present widely used UAV navigation means is a GPS navigation; Certain environment limitation that has owing to its use; Navigate mode (TRN) based on landform had appearred afterwards; Carry active sensor (radar, laser) or passive sensor (camera) actual measurement landform and priori topomap through carrier and mate, it is relative position and a speed of confirming carrier according to environmental information (landform, mark).Landform navigational system such as landform isoline navigation (TERCOM), digital scene zone correlation navigation (DSMAC) are also being used.

In the last few years, a large amount of scientific researches concentrated on the air navigation aid research of no GPS, as utilized laser sensor to keep away barrier and indoor positioning.Because vision sensor is passive, and the advantage on cost, weight, power consumption and size, become the first-selection that substitutes GPS navigation.The visual information air navigation aid of utilizing the flight carrier is that the vision navigation method of ground carrier is introduced the earliest, as being to go for and follow the tracks of the road sign of storage in advance based on image algorithm.Before carrier flight,, be stored in lane database to road sign and positional information in advance through the route of planning.When carrier flies, compare with the road sign in the database through the characteristic that airborne camera is observed, after mating successfully, carrier just can be estimated out with respect to the position and the attitude information of road sign, thereby is obtained navigational parameter.But, the confirming of road sign that it need be predicted and positional information, and plurality of applications occasion observation information or predict observation information generation great change in advance not.In practical application, often need unmanned plane to go deep into the unknown complex environment and go to accomplish detection, supervision, tracking or strike mission, can't think in advance ground control point is set.Therefore, research do not receive prior imformation constraint, independently to seek the air navigation aid that the nature terrestrial reference carries out vision guided navigation error correction be the prerequisite that ensures that unmanned plane is executed the task smoothly under the complicated circumstances not known.

Navigation algorithm such as two-dimentional SLAM algorithm are the methods of locating simultaneously and drawing, according to measurement features and positional information in the circumstances not known; Estimate navigational parameter in the circumstances not known, although the SLAM algorithm than more efficient, is used for UAV (computation-bound situation); Two bottlenecks are arranged, and at first vision SLAM algorithm needs observed object to be followed the tracks of a period of time, secondly; Along with the increase of road sign, the calculated amount of SLAM algorithm and computing time increase huge.Also have certain methods that specific natural landmark is extracted its invariant features point, utilize the method for unique point cluster to discern the judgement road sign.These class methods have stronger robustness, can be applied in the complex environment, are the developing direction of natural landmark navigation, but general calculated amount is also bigger, are difficult to satisfy the order that requires of real-time.

The SIFT algorithm has the unchangeability at good yardstick, rotation, illumination and three-dimensional visual angle, thereby the SIFT unique point has good differentiation property, is well suited for being used for the characteristics of image coupling.Because the flight of aircraft causes a certain moment of some characteristic in the image sequence to get into image; The a certain moment is walked out image again; So positional information of utilizing these characteristics of image to calculate; The synthetic vectors flight path is also carried out data fusion with the inertial navigation positional information, obtains the navigational parameter of high-quality.

Therefore, route synthetic method in the unmanned plane vision navigation of the present invention's research for the high position precision that is fit to middle-size and small-size unmanned plane, the microminiaturized characteristics cheaply that reach, has theory and practical value just.

Summary of the invention

The flight path composition problem of primary study unmanned plane vision navigational system of the present invention.When utilizing the characteristics of image coupling to obtain navigation information, there is individual problem not ignore, that is exactly the rotation problem of unmanned plane, the i.e. variable effect of unmanned plane height and angle.The present invention proposes to utilize the Eulerian angle and the angular rate compensation rotation effect of inertial navigation system measurement, then according to the synthetic complete flight path based on visual information of the movement locus of road sign in the image.Promptly utilize image (pixel displacement) the coordinate transform relation of natural landmark in the certain hour interval to calculate the positional information of unmanned plane.Concrete research approach is as shown in Figure 1.Main contents are following:

1) unmanned plane rotation effect compensation

2) flight path is synthetic

Description of drawings

Fig. 1 is research approach figure of the present invention.

Fig. 2 is a flight path unique point synoptic diagram.

Embodiment

The concrete mentality of designing of key link is following:

(1) unmanned plane rotation effect compensation

The rotation effect of unmanned plane is influential to unique point displacement in the image.So after characteristic point position information, remove the influence of rotation effect.Utilize the Eulerian angle that inertial navigation system measures (θ, φ) and angular velocity (ω _x, ω _y, ω _z), based on formula (1) and formula (2).

$\left\{\begin{array}{c}{x}_i^t=x_i-\left(f\tan \mathrm{\θ}\right)\\ y_i^t=y_i-\left(f\tan \mathrm{\φ}\right)\end{array}\right.---\left(1\right)$

And $\left\{\begin{array}{c}{\stackrel{\·}{x}}_i^t={\stackrel{\·}{x}}_i-(\frac{x_i{y}_i}{f}{\mathrm{\ω}}_x-\frac{f^2+x_i^2}{f}{\mathrm{\ω}}_y+y_i{\mathrm{\ω}}_z)\\ {\stackrel{\·}{y}}_i^t={\stackrel{\·}{y}}_i-(\frac{f^2+y_i^2}{f}{\mathrm{\ω}}_x-\frac{x_i{y}_i}{f}{\mathrm{\ω}}_y-x_i{\mathrm{\ω}}_z)\end{array}\right.---\left(2\right)$

Wherein f is a camera focus, and

is the characteristics of image velocity of displacement.

1) flight path is synthetic

After utilizing visual information to determine the positional information of natural landmark, synthetic complete flight path of the movement locus of road sign in the image of giving chapter and verse based on visual information.Promptly utilize image (pixel displacement) the coordinate transform relation of natural landmark in the certain hour interval to calculate the positional information of unmanned plane.Its unique point signal is shown in Figure 2.

Step 1: the location compute under the image coordinate system.It is that center, old characteristic shift out image and new characteristic (round characteristic) shift-in image that three sub-graphs among Fig. 2 have been represented respectively with old unique point (three corner characteristics), and reaching with the new feature is the picture displacement process at center.Then under image coordinate, the t total displacement of image sequence constantly be on the t time chart picture each unique point displacement with, shown in formula (3).

$\left\{\begin{array}{c}{x}^t=\underset{t=1}{\overset{i=n}{\mathrm{\Σ}}}{x}_i^t\\ y^t=\underset{t=1}{\overset{i=n}{\mathrm{\Σ}}}{y}_i^t\end{array}\right.---\left(3\right)$

Step 2: aircraft and feature pitch resolve from Z.Characteristic displacement speed

Relation between the distance is based on the light stream principle therewith, i.e. characteristic displacement speed (pixel speed) and focal length of camera f and aircraft speed v _x, v _y, v _zBetween relation shown in formula 4.

$\left\{\begin{array}{c}{\stackrel{\·}{x}}_i^t=f\frac{v_x}{z}+x_i\frac{v_z}{z}\\ {\stackrel{\·}{y}}_i^t=f\frac{v_y}{z}+y_i\frac{v_z}{z}\end{array}\right.---\left(4\right)$

Formula (4) carries out differential to the time, can get

$\left\{\begin{array}{c}{\stackrel{\·\·}{x}}_i^t=f\frac{a_x}{z}\\ {\stackrel{\·\·}{y}}_i^t=f\frac{a_y}{z}\end{array}\right.---\left(5\right)$

A wherein _x, a _yAircraft inertial navigation device is measured the acceleration of carrier.Formula (5) is apart from the solution formula between Z and characteristic displacement speed.

Step 3: the Position And Velocity information of synthetic aircraft.The distance of utilizing step 2 to calculate

And the horizontal level of the scaling method calculating aircraft of camera (X, Y) and speed (v _x, v _y), shown in formula (6).

It is the situation of constant that formula (6) is applicable to apart from Z, during different distance Z, shown in formula (7).

Step 4:kalman filtering realizes that navigation data merges.Select (X, Y, Z, v _x, v _y, v _z) be state variable, select

Inertial navigation acceleration (a _x, a _y, a _z) be input variable, design kalman wave filter.

The invention has the advantages that, abandon " definitely " scene matching aided navigation of real-time figure and reference map, transfer to adopt the dynamic key images of real-time figure and real-time figure to carry out " relatively " scene matching aided navigation, overcome the very difficulty of rareness of non-adaptive district image metric characteristic.On the other hand, merging mutually with inertial navigation more to provide flight carrier navigational parameter in all directions, and this research all has certain theory and learning value to aircraft navigation and ground navigation, has a good application prospect.

Claims (3)

1. the flight path synthetic method of a unmanned plane vision navigational system.It is characterized in that (1) solves the variable effect of unmanned plane height and angle; (2) utilize image (pixel displacement) the coordinate transform relation of natural landmark in the certain hour interval to calculate the positional information of unmanned plane.

2. the flight path synthetic method of a kind of unmanned plane vision navigational system according to claim 1 is characterized in that, the Eulerian angle and the angular rate compensation rotation that utilize inertial navigation system to measure are imitated, and solve the variable effect of unmanned plane height and angle.

3. the flight path synthetic method of a kind of unmanned plane vision navigational system according to claim 1; It is characterized in that; The synthetic method of unmanned plane positional information is based on the light stream principle; Relation by unique point pixel displacement, camera focus, unique point and carrier distance leave is resolved, and by the synthetic flight path of kalman filtering.

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